# Курсы ## Курсы, которые надо пройти * [Deep Learning Google](https://eu.udacity.com/course/deep-learning--ud730) * [Machine Learning Crash Course with TensorFlow APIs](https://developers.google.com/machine-learning/crash-course/) * [Learning TensorFlow](https://learningtensorflow.com) * [Kaggel Learn](https://www.kaggle.com/learn/overview) * [Data Vizualization Kaggle](https://www.kaggle.com/learn/data-visualisation) * Andrew Ng * cs221 * Future Learning * [HSE Course (GitHub)](https://github.com/esokolov/ml-course-hse/) ## Stepic Additional * [Examination](https://stepik.org/lesson/68008/step/1?unit=44971) * [Adaptive tasks](https://stepik.org/lesson/43732/step/1?adaptive=true&unit=22777) ## Курсы, что я прохожу * ODS ML Course Open * Deep NLP MIPT * cs224n (NLP) ## Курсы, что я уже прошел ----- # Чтение ## Штуки, что надо прочитать * [How Numba and Cython speed up Python code](https://rushter.com/blog/numba-cython-python-optimization/) * [Serving machine learning models with RestServe on R](http://restrserve.org/serving-ml.html) * [R TensorFlow Tutorial](https://tensorflow.rstudio.com) * [R Keras Tutorial](https://keras.rstudio.com) * [New Resources for Deep Learning with the Neuromation Platform](https://medium.com/neuromation-io-blog/new-resources-for-deep-learning-with-the-neuromation-platform-55fd411cb440) * [Word2Vec Tutorial](http://mccormickml.com/2016/04/19/word2vec-tutorial-the-skip-gram-model/) * [Серия статей про ембединги текста](http://ruder.io/word-embeddings-1/) * [ImageNet Classification with Deep Convolutional Neural Networks - Colyer](https://blog.acolyer.org/2016/04/20/imagenet-classification-with-deep-convolutional-neural-networks/) * [Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition](https://blog.acolyer.org/2016/04/19/context-dependent-pre-trained-deep-neural-networks-for-large-vocabulary-speech-recognition/) * https://habrahabr.ru/post/352632/ Истинная реализация нейросети с нуля. * [Functional Programming for Deep Learning](https://www.notion.so/metya/5f25295584414592a3581836625b77d3#d5f53eac3e7146eeba6bf6365449600a) ----- # Видео ## Штуки, что я прочитал ## Видео, что мне надо посмотреть * [Essense of Linear Azlgebra](https://www.youtube.com/watch?v=kjBOesZCoqc&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab) * [PyData Meetup (TensorFlow Architecture)](https://www.youtube.com/watch?v=aoin1nl_eSA&feature=youtu.be&t=5810) [Materials](https://github.com/yurijvolkov/pydata_examples) * [Kaggle Mercedes Benz: предсказание времени тестирования автомобилей ](https://www.youtube.com/watch?v=HT3QpRp2ewA) * [Эффективные модели ближайших соседей](https://www.youtube.com/watch?v=UUm4MOyVTnE) ## Видео, что я посмотрел * [NLP натекин](https://www.youtube.com/watch?v=Ozm0bEi5KaI)